Not that long ago, big data analytics was a burgeoning technology, understood and practiced by a relatively small number of technologically savvy companies. In just a few years time, though, big data analytics has firmly cemented its place as a critical business tool, essential for organizations in virtually every industry. With analytics, firms can gain invaluable insight from otherwise unusable unstructured and semistructured data.

The potential rewards from analytics have led companies to invest much more time and effort toward collecting, generating and internally sharing big data from a variety of sources.

However, as beneficial as big data analytics has proven to be, there are a number of issues which firms must overcome to successfully utilize this resource. One obstacle, highlighted recently by CSO Online contributor John Mello, Jr., is data security.

Big data and security
Data security is a key concern for every business. If a company's data is not safe, the organization will be at risk of suffering a data breach. Breaches can be caused by inadvertent insider errors or through the efforts of malicious cyberattackers. As companies have begun to truly appreciate the value inherent to big data, so, too, have criminals, who now will frequently target companies to steal this information for corporate espionage purposes.

The problem, according to Mello, is that "the network architecture that supports big data wasn't created with security in mind." Consequently, the use of big data analytics can potentially pose a risk for overall corporate data security.

Mello pointed out that traditional data protection methods often rely on establishing a perimeter. But according to a recent Zettaset white paper, such approaches are not able to effectively secure big data sets. Because they are designed to protect a single database, rather than the numerous databases inherent to big data, traditional security is often overburdened.

"When you put [traditional security products] on a large scale distributed computing environment, they become either a choke point or a single point of failure for the entire cluster," explained Brian Christian, CTO of Zettaset, in an interview with Mello.

Another issue, highlighted by Jason Escaravage, a principal with Booz Allen Hamilton, is the fact that when existing data security is added to big data systems, the result is often diminished performance.

"Security can be an enabler, but if it's done poorly or it's not factored into the original designs, it can absolutely slow things down," said Escaravage, Mello reported. "It can absolutely cause all kinds of terrible things to happen to the solution."

The right solution
These problems emphasize the need for firms hoping to leverage big data analytics to invest in big-data specific secure file transfer solutions. High quality data transfer tools can allow a company to leverage its big data resources without posing as a security risk, and without sacrificing productivity or efficiency. Additionally, these tools can and should be flexible, allowing a firm to move its big data as needed, regardless of time or the size of the data sets.